The detection of non-O157 E. coli in food by immunomagnetic separation
Bibliographic record
Abstract
AIMS: To compare immunomagnetic separation (IMS) protocols (enrichment media and temperature) for the isolation of Escherichia coli serotypes O26 and O111 from four different foods. METHODS AND RESULTS: Foods (minced beef, cheese, apple juice and pepperoni) spiked with low numbers (<100 g(-1)) of stressed nalidixic mutant E. coli serotypes O26 and O111 were enriched in media based on buffered peptone water (BPW), tryptone soya and EC broths incubated at temperatures of 37 and 42 degrees C to optimize the IMS technique. BPW enrichments gave increased recoveries of both serotypes compared with tryptone soya and EC broths. Elevated temperatures of incubation at 42 degrees C were superior to 37 degrees C. CONCLUSIONS: Positive detection of low numbers of stressed target pathogens in all replicate tests was only possible using BPW enrichments. The majority of tests from alternative enrichments resulted in zero or single colonies recovered post-IMS. SIGNIFICANCE AND IMPACT OF THE STUDY: The optimum IMS protocol would improve isolation rates of E. coli O26 and O111 from foods and lead to increased safety for the consumer. Sub-optimal IMS protocols could lead to foods being incorrectly labelled free from these pathogens.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".